from datetime import timedelta
from utils.operators.cluster_for_spark_sql_operator import SparkSqlOperator
from jms.dwd.dwd_wide_tms_trunk_shipno_road_waybill_dt import jms_dwd__dwd_wide_tms_trunk_shipno_road_waybill_dt
from jms.dim.dim_lmdm_sys_network import jms_dim__dim_lmdm_sys_network
from jms.dim.dim_sys_manage_region import jms_dim__dim_sys_manage_region
from jms.dim.dim_tms_mainline_vehicleloading import jms_dim__dim_tms_mainline_vehicleloading
from jms.dm.dm_tms_shipment_noweight_detail_dt import  jms_dm__dm_tms_shipment_noweight_detail_dt
from jms.dwd.tab.dwd_tab_barscan_cycle_transfer_record_base_dt import jms_dwd__dwd_tab_barscan_cycle_transfer_record_base_dt
from jms.dwd.tms.dwd_tmsnew_shipment_stop_union_base_dt import jms_dwd__dwd_tmsnew_shipment_stop_union_base_dt
from jms.dm.dm_trunk_error_scan_detail import jms_dm__dm_trunk_error_scan_detail
from jms.dim.tms.dim_yl_tms_route_base_dt import jms_dim__dim_yl_tms_route_base_dt
from jms.dim.dim_network_whole_massage import jms_dim__dim_network_whole_massage

# 配置所依赖的表所处的[任务名字]及[任务所在包的位置]

jms_dm__dm_tms_trunk_load_factor_basic_dt = SparkSqlOperator(
    task_id='jms_dm__dm_tms_trunk_load_factor_basic_dt',
    task_concurrency=1,
    pool_slots=2,
    master='yarn',
    execution_timeout=timedelta(minutes=20),
    email=['yushuo@jtexpress.com','yl_bigdata@yl-scm.com'],
    name='jms_dm__dm_tms_trunk_load_factor_basic_dt_{{ execution_date | date_add(1) | cst_ds }}',
    sql='jms/dm/dm_tms_trunk_load_factor_basic_dt/execute.hql',
    driver_memory='2G',
    driver_cores=2,
    executor_cores=2,
    executor_memory='2G',
    num_executors=6,  # spark.dynamicAllocation.enabled 为 True 时，num_executors 表示最少 Executor 数
    conf={'spark.dynamicAllocation.enabled': 'true',  # 动态资源开启
          'spark.shuffle.service.enabled': 'true',  # 动态资源 Shuffle 服务开启
          #'spark.dynamicAllocation.maxExecutors': 50,  # 动态资源最大扩容 Executor 数
          'spark.dynamicAllocation.maxExecutors': 16,  # 动态资源最大扩容 Executor 数
          'spark.dynamicAllocation.cachedExecutorIdleTimeout': 180,  # 动态资源自动释放闲置 Executor 的超时时间(s)
          'spark.sql.sources.partitionOverwriteMode': 'dynamic',  # 允许删改已存在的分区
          'spark.executor.memoryOverhead': '1G',  # 堆外内存
          'spark.sql.shuffle.partitions': 1000,
          'spark.hadoop.hive.exec.dynamic.partition.mode': 'true',
          'spark.network.timeout': 900,
          'spark.core.connection.ack.wait.timeout': 300,
          },
    hiveconf={'hive.exec.dynamic.partition': 'true',  # 动态分区
              'hive.exec.dynamic.partition.mode': 'nonstrict',
              'hive.exec.max.dynamic.partitions': 20,  # 每天生成 20 个分区
              'hive.exec.max.dynamic.partitions.pernode': 20,  # 每天生成 20 个分区
              'hive.merge.mapredfiles':'true',
              'hive.merge.mapfiles':'true',
              'hive.merge.size.per.task': 128000000,
              "hive.merge.smallfiles.avgsize":128000000,
              },
    yarn_queue='pro',
)
# 设置依赖
jms_dm__dm_tms_trunk_load_factor_basic_dt << [
    jms_dwd__dwd_wide_tms_trunk_shipno_road_waybill_dt,
    jms_dim__dim_lmdm_sys_network,
    jms_dim__dim_sys_manage_region,
    jms_dim__dim_tms_mainline_vehicleloading,
    jms_dm__dm_tms_shipment_noweight_detail_dt,
    jms_dm__dm_trunk_error_scan_detail,
    jms_dwd__dwd_tmsnew_shipment_stop_union_base_dt,
    jms_dwd__dwd_tab_barscan_cycle_transfer_record_base_dt,
    jms_dim__dim_yl_tms_route_base_dt,
jms_dim__dim_network_whole_massage
]
